What are the Consequences of Incorrect Sample Size?
Using an incorrect sample size can have significant implications:
Underpowered Studies: An insufficient sample size may lead to a failure to detect a true effect, resulting in Type II errors (false negatives). Overpowered Studies: An excessively large sample size may detect trivial effects that are not practically significant, leading to Type I errors (false positives). Resource Wastage: Oversampling can lead to unnecessary expenditure of time, money, and effort.
